🔍 Data briefing

The data contains total 110 valid observations(remove the rows where volume is equal to zero all the time) within 22 specific items spreading in 5 regions(ADE BRI MEL PER SYD).

Here is the glimpse of the converted data in long format :

## tibble [4,730 × 14] (S3: tbl_df/tbl/data.frame)
##  $ Item & Region    : chr [1:4730] "1234ADE" "1234ADE" "1234ADE" "1234ADE" ...
##  $ Region           : chr [1:4730] "ADE" "ADE" "ADE" "ADE" ...
##  $ Item Code        : Factor w/ 22 levels "1234","1235",..: 1 1 1 1 1 1 1 1 1 1 ...
##  $ Item Description : chr [1:4730] "Item 1234" "Item 1234" "Item 1234" "Item 1234" ...
##  $ Group            : chr [1:4730] "10PB" "10PB" "10PB" "10PB" ...
##  $ Supplier         : chr [1:4730] "1YA" "1YA" "1YA" "1YA" ...
##  $ Pack Qty         : num [1:4730] 60 60 60 60 60 60 60 60 60 60 ...
##  $ Pack cubic metres: num [1:4730] 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 ...
##  $ E.O.Q.           : num [1:4730] 1200 1200 1200 1200 1200 1200 1200 1200 1200 1200 ...
##  $ Cost             : num [1:4730] 5.97 5.97 5.97 5.97 5.97 5.97 5.97 5.97 5.97 5.97 ...
##  $ Month            : chr [1:4730] "Oct" "Nov" "Dec" "Jan" ...
##  $ Year             : chr [1:4730] "2020" "2020" "2020" "2021" ...
##  $ Volume           : num [1:4730] 960 660 840 1260 120 900 840 1020 480 780 ...
##  $ Yearmonth        : mth [1:4730] 2020 Oct, 2020 Nov, 2020 Dec, 2021 Jan, 2021 Feb, 2021 Ma...

Pattern learning

📈 Historical pattern

If displaying all data at once on the canvas will result in visual clutter and make it difficult to analyze the data intuitively, therefore, in the drawing part, only 10 sampled products will be displayed. However, in the backend calculations, all items will still be considered.the principle of the sample selection will based on the overall average volume of goods,by choosing the top three, middle four, and bottom four items, below is the item code I select for example:

Here is

📊 Historical pattern